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Physics-informed deep operator networks for structural damage identification via damage function
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DOI：10.1016/j.ijfatigue.2026.109856.png)
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Abstract
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• A physics-informed deep operator framework integrating a damage function is proposed for structural damage identification. • A bilevel alternating optimization strategy decouples network training and damage parameter updating. • Structural damage is represented by a continuous damage function for robust reconstruction of stiffness degradation fields.
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